CULaneDbInspector.py

import scipy.io
import numpy as np
import cv2
import os
from tqdm import tqdm
import argparse


def walkThroughDataset(dataSetDir):
    trainIndexFilePath = os.path.join(dataSetDir, r'list\train_gt.txt')

    trainFilePairList = []

    with open(trainIndexFilePath, 'r') as f:
        for line in f.readlines():
            imagePath, segImagePath, lane0, lane1, lane2, lane4 = line.split()
            trainFilePairList.append(
                (os.path.join(dataSetDir, imagePath[1:]), os.path.join(dataSetDir, segImagePath[1:]), lane0, lane1, lane2, lane4))

    colorMapMat = np.zeros((5, 3), dtype=np.uint8)

    for i in range(0, 5):
        if i != 0:
            colorMapMat[i] = np.random.randint(0, 255, dtype=np.uint8, size=3)

    for imageFile, segFile, _, _, _, _ in tqdm(trainFilePairList):
        img_bgr = cv2.imread(imageFile)
        seg = cv2.imread(segFile,cv2.IMREAD_UNCHANGED)
        segImage = colorMapMat[seg]

        res = cv2.addWeighted(img_bgr, 0.7, segImage, 0.7, 0.4)
        cv2.imshow('CULane Dataset Quick Inspector', res)
        k = cv2.waitKey(1) & 0xff
        if k == 27:
            break
    cv2.destroyWindow('CULane Dataset Quick Inspector')


def parse_args():
    parser = argparse.ArgumentParser(
        description='CULane Dataset Quick Inspector')
    parser.add_argument('--rootDir', type=str, default=r'E:\CULane',
                        help='root directory (default: E:\\CULane)')
    args = parser.parse_args()                    
    return args

if __name__ == '__main__':
    args = parse_args()
    walkThroughDataset(args.rootDir)